Evidence map›Paper›PMID 37763879›Full record

ArticleMicromachines2023

Temperature Drift Compensation of Fiber Optic Gyroscopes Based on an Improved Method.

Xinwang Wang, Ying Cui, Huiliang Cao

Abstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xinwang WangSchool of Instrument Science and Engineering, Southeast University, Nanjing 210018, China.
Ying CuiSchool of Automotive and Transportation, Wuxi Institute of Technology, Wuxi 214000, China.
Huiliang CaoKey Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China.ORCID 0000-0001-9862-4329

Funding

Aeronautical Science Foundation of China 2019080U0002Fundamental Research Program of Shan-xi Province 20210302123020Fundamental Research Program of Shan-xi Province 20210302123062Key Research and Development (R&D) Projects of Shanxi Province 201903D111004National defense basic scientific research program WDZC20190303National Key Research and Development Program of China SQ2022YFB3200085National Natural Science Foundation of China 51705477Pre-Research Field Foundation of Equipment Development Department of China 61405170104Pre-Research Field Foundation of Equipment Development Department of China 80917010501Shanxi "1331 Project" Key Subjects Construction U2230206Shanxi province key laboratory of quantum sensing and precision measurement 201905D121001Technology Field Fund of Basic Strengthening Plan of China 2020JCJQJJ409Technology Field Fund of Basic Strengthening Plan of China 2021-JCJQ-JJ-0315
6 · The paper itself

Abstract

This study proposes an improved multi-scale permutation entropy complete ensemble empirical mode decomposition with adaptive noise (MPE-CEEMDAN) method based on adaptive Kalman filter (AKF) and grey wolf optimizer-least squares support vector machine (GWO-LSSVM). By establishing a temperature compensation model, the gyro temperature output signal is optimized and reconstructed, and a gyro output signal is obtained with better accuracy. Firstly, MPE-CEEMDAN is used to decompose the FOG output signal into several intrinsic mode functions (IMFs); then, the IMFs signal is divided into mixed noise, temperature drift, and other noise according to different frequencies. Secondly, the AKF method is used to denoise the mixed noise. Thirdly, in order to denoise the temperature drift, the fiber gyroscope temperature compensation model is established based on GWO-LSSVM, and the signal without temperature drift is obtained. Finally, the processed mixed noise, the processed temperature drift, the processed other noise, and the signal-dominated IMFs are reconstructed to acquire the improved output signal. The experimental results show that, by using the improved method, the output of a fiber optic gyroscope (FOG) ranging from -30 °C to 60 °C decreases, and the temperature drift dramatically declines. The factor of quantization noise (Q) reduces from 6.1269 × 10

Indexed as

adaptive Kalman filter (AKF)fiber optic gyroscope (FOG)grey wolf optimizer-least squares support vector machine (GWO-LSSVM)multi-scale permutation entropy complete ensemble empirical mode decomposition with adaptive noise (MPE-CEEMDAN)temperature compensation

Identifiers

PMID37763879
PMCPMC10536931

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.